Spectral Methods for Linear and Non-Linear Semi-Supervised Dimensionality Reduction

Abstract

We present a general framework of spectral methods for semi-supervised dimensionality reduction. Applying an approach called manifold regularization, our framework naturally generalizes existent supervised frameworks. Furthermore, by our two semi-supervised versions of the representer theorem, our framework can be kernelized as well. Using our framework, we… (More)

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Cite this paper

@article{Chatpatanasiri2008SpectralMF, title={Spectral Methods for Linear and Non-Linear Semi-Supervised Dimensionality Reduction}, author={Ratthachat Chatpatanasiri}, journal={CoRR}, year={2008}, volume={abs/0804.0924} }